DeconvDLModel-class     The DeconvDLModel Class
PropCellTypes-class     The PropCellTypes Class
SpatialDDLS-Rpackage    SpatialDDLS: an R package to deconvolute
                        spatial transcriptomics data using deep neural
                        networks
SpatialDDLS-class       The SpatialDDLS Class
ZinbParametersModel-class
                        The Class ZinbParametersModel
barErrorPlot            Generate bar error plots
barPlotCellTypes        Bar plot of deconvoluted cell type proportions
blandAltmanLehPlot      Generate Bland-Altman agreement plots between
                        predicted and expected cell type proportions of
                        test data
calculateEvalMetrics    Calculate evaluation metrics on test mixed
                        transcriptional profiles
cell.names              Get and set 'cell.names' slot in a
                        'PropCellTypes' object
cell.types              Get and set 'cell.types' slot in a
                        'DeconvDLModel' object
corrExpPredPlot         Generate correlation plots between predicted
                        and expected cell type proportions of test data
createSpatialDDLSobject
                        Create a 'SpatialDDLS' object
deconv.spots            Get and set 'deconv.spots' slot in a
                        'SpatialExperiment' object
deconvSpatialDDLS       Deconvolute spatial transcriptomics data using
                        trained model
distErrorPlot           Generate box or violin plots showing error
                        distribution
estimateZinbwaveParams
                        Estimate parameters of the ZINB-WaVE model to
                        simulate new single-cell RNA-Seq expression
                        profiles
features                Get and set 'features' slot in a
                        'DeconvDLModel' object
genMixedCellProp        Generate training and test cell type
                        composition matrices
getProbMatrix           Getter function for the cell composition matrix
installTFpython         Install Python dependencies for SpatialDDLS
interGradientsDL        Calculate gradients of predicted cell
                        types/loss function with respect to input
                        features for interpreting trained deconvolution
                        models
loadSTProfiles          Loads spatial transcriptomics data into a
                        SpatialDDLS object
loadTrainedModelFromH5
                        Load from an HDF5 file a trained deep neural
                        network model into a 'SpatialDDLS' object
method                  Get and set 'method' slot in a 'PropCellTypes'
                        object
mixed.profiles          Get and set 'mixed.profiles' slot in a
                        'SpatialExperiment' object
model                   Get and set 'model' slot in a 'DeconvDLModel'
                        object
plotDistances           Plot distances between intrinsic and extrinsic
                        profiles
plotHeatmapGradsAgg     Plot a heatmap of gradients of classes / loss
                        function wtih respect to the input
plotSpatialClustering   Plot results of clustering based on predicted
                        cell proportions
plotSpatialGeneExpr     Plot normalized gene expression data (logCPM)
                        in spatial coordinates
plotSpatialProp         Plot predicted proportions for a specific cell
                        type using spatial coordinates of spots
plotSpatialPropAll      Plot predicted proportions for all cell types
                        using spatial coordinates of spots
plotTrainingHistory     Plot training history of a trained SpatialDDLS
                        deep neural network model
plots                   Get and set 'plots' slot in a 'PropCellTypes'
                        object
preparingToSave         Prepare 'SpatialDDLS' object to be saved as an
                        RDA file
prob.cell.types         Get and set 'prob.cell.types' slot in a
                        'SpatialExperiment' object
prob.matrix             Get and set 'prob.matrix' slot in a
                        'PropCellTypes' object
project                 Get and set 'project' slot in a
                        'SpatialExperiment' object
saveRDS                 Save 'SpatialExperiment' objects as RDS files
saveTrainedModelAsH5    Save a trained 'SpatialDDLS' deep neural
                        network model to disk as an HDF5 file
set                     Get and set 'set' slot in a 'PropCellTypes'
                        object
set.list                Get and set 'set.list' slot in a
                        'PropCellTypes' object
showProbPlot            Show distribution plots of the cell proportions
                        generated by 'genMixedCellProp'
simMixedProfiles        Simulate training and test mixed spot profiles
simSCProfiles           Simulate new single-cell RNA-Seq expression
                        profiles using the ZINB-WaVE model parameters
single.cell.real        Get and set 'single.cell.real' slot in a
                        'SpatialExperiment' object
single.cell.simul       Get and set 'single.cell.simul' slot in a
                        'SpatialExperiment' object
spatial.experiments     Get and set 'spatial.experiments' slot in a
                        'SpatialExperiment' object
spatialPropClustering   Cluster spatial data based on predicted cell
                        proportions
test.deconv.metrics     Get and set 'test.deconv.metrics' slot in a
                        'DeconvDLModel' object
test.metrics            Get and set 'test.metrics' slot in a
                        'DeconvDLModel' object
test.pred               Get and set 'test.pred' slot in a
                        'DeconvDLModel' object
topGradientsCellType    Get top genes with largest/smallest gradients
                        per cell type
trainDeconvModel        Train deconvolution model for spatial
                        transcriptomics data
trained.model           Get and set 'trained.model' slot in a
                        'SpatialExperiment' object
training.history        Get and set 'training.history' slot in a
                        'DeconvDLModel' object
zinb.params             Get and set 'zinb.params' slot in a
                        'SpatialExperiment' object
zinbwave.model          Get and set 'zinbwave.model' slot in a
                        'ZinbParametersModel' object
